A small-scale experiment using microwave interferometry to investigate detonation and shock-to-detonation transition in pressed TATB

A small-scale characterization test utilizing microwave interferometry was developed to dynamically measure detonation and run to detonation distance in explosives. The technique was demonstrated by conducting two experimental series on the well-characterized explosive triaminotrinitrobenzene (TATB). In the first experiment series, the detonation velocity was observed at varying porosity. The velocity during TATB detonation matched well with predictions made using CHEETAH and an empirical relation from the Los Alamos National Laboratory (LANL). The microwave interferometer also captured unsteady propagation of the reaction when a low density charge was near the failure diameter. In the second experiment series, Pop-plots were produced using data obtained from shock initiation of the TATB through a polymethyl methacrylate (PMMA) attenuator. The results compared well to wedge test data from LANL despite the microwave interferometer test being of substantially smaller scale. The results showed the test method is attractive for rapid characterization of new and improvised explosive materials

Primary Challengers: Examining Competition in U.S. House Primary Elections with Female Candidates

Previous research has established that voters and political elites hold gendered stereotypes toward female candidates. Additionally, traditional family roles and gendered expectations are found to affect the self-confidence of women and their political ambition. However, little is known about how potential challengers perceive women as candidates. To fill this gap, I examine whether the presence of a woman in a primary election influences the entry of prospective candidates. Are women perceived to be more vulnerable candidates, thus attracting more competition in primary elections? To answer this, I estimate a negative binomial regression with primary election data for the U.S. House of Representatives from 2002-2012. The results confirm previous findings that women face more primary competition, especially Republican women. However, Democratic incumbents and women who fundraise large amounts of money deter challengers from entering the primary election, suggesting they are viewed as stronger candidates, thus dissuading potential candidates from entering the race. To further examine these results I estimate the propensity score of congressional districts and match a random sample of my population to compare candidate-filing dates. The results suggest women strategically enter a race when there are fewer candidates. Furthermore, I find evidence that challengers are more likely to enter a primary election after a woman declares candidacy

A Generalized Spatial Measure for Resilience of Microbial Systems

The emergent property of resilience is the ability of a system to return to an original state after a disturbance. Resilience may be used as an early warning system for significant or irreversible community transition; that is, a community with diminishing or low resilience may be close to catastrophic shift in function or an irreversible collapse. Typically, resilience is quantified using recovery time, which may be difficult or impossible to directly measure in microbial systems. A recent study in the literature showed that under certain conditions, a set of spatial-based metrics termed recovery length, can be correlated to recovery time, and thus may be a reasonable alternative measure of resilience. However, this spatial metric of resilience is limited to use for step-change perturbations. Building upon the concept of recovery length, we propose a more general form of the spatial metric of resilience that can be applied to any shape of perturbation profiles (for example, either sharp or smooth gradients). We termed this new spatial measure “perturbation-adjusted spatial metric of resilience” (PASMORE). We demonstrate the applicability of the proposed metric using a mathematical model of a microbial mat

Integrating Ecological and Engineering Concepts of Resilience in Microbial Communities

Many definitions of resilience have been proffered for natural and engineered ecosystems, but a conceptual consensus on resilience in microbial communities is still lacking. We argue that the disconnect largely results from the wide variance in microbial community complexity, which range from compositionally simple synthetic consortia to complex natural communities, and divergence between the typical practical outcomes emphasized by ecologists and engineers. Viewing microbial communities as elasto-plastic systems that undergo both recoverable and unrecoverable transitions, we argue that this gap between the engineering and ecological definitions of resilience stems from their respective emphases on elastic and plastic deformation, respectively. We propose that the two concepts may be fundamentally united around the resilience of function rather than state in microbial communities and the regularity in the relationship between environmental variation and a community\u27s functional response. Furthermore, we posit that functional resilience is an intrinsic property of microbial communities and suggest that state changes in response to environmental variation may be a key mechanism driving functional resilience in microbial communities

Identifying metabolites from protein identifiers with P2M

The identification of metabolites from complex biological samples often involves matching experimental mass spectrometry data to signatures of compounds derived from massive chemical databases. However, misidentifications may result due to the complexity of potential chemical space that leads to databases containing compounds with nearly identical structures. Prior knowledge of compounds that may be enzymatically consumed or produced by an organism can help reduce misidentifications by restricting initial database searching to compounds that are likely to be present in a biological system. While databases such as UniProt allow for the identification of small molecules that may be consumed or generated by enzymes encoded in an organism's genome, currently no tool exists for identifying SMILES strings of metabolites associated with protein identifiers and expanding R-containing substructures to fully defined, biologically relevant chemical structures. Here we present Proteome2Metabolome (P2M), a tool that performs these tasks using external database querying behind a simple command line interface. Beyond mass spectrometry based applications, P2M can be generally used to identify biologically relevant chemical structures likely to be observed in a biological system